Error with indexing 2D lat/lon coordinates #4090

filslp = "ChonghuaYinData/prmsl.mon.mean.nc"
filtmp = "ChonghuaYinData/air.sig995.mon.mean.nc"
filprc = "ChonghuaYinData/precip.mon.mean.nc"

ds_slp = xr.open_dataset(filslp).sel(time=slice(str(yrStrt)+'-01-01', str(yrLast)+'-12-31'))

ds_slp

<xarray.Dataset>
Dimensions:            (nbnds: 2, time: 480, x: 349, y: 277)
Coordinates:
  * time               (time) datetime64[ns] 1979-01-01 ... 2018-12-01
    lat                (y, x) float32 ...
    lon                (y, x) float32 ...
  * y                  (y) float32 0.0 32463.0 64926.0 ... 8927325.0 8959788.0
  * x                  (x) float32 0.0 32463.0 64926.0 ... 11264660.0 11297120.0
Dimensions without coordinates: nbnds
Data variables:
    Lambert_Conformal  int32 ...
    prmsl              (time, y, x) float32 ...
    time_bnds          (time, nbnds) float64 ...
Attributes:
    Conventions:    CF-1.2
    centerlat:      50.0
    centerlon:      -107.0
    comments:       
    institution:    National Centers for Environmental Prediction
    latcorners:     [ 1.000001  0.897945 46.3544   46.63433 ]
    loncorners:     [-145.5       -68.32005    -2.569891  148.6418  ]
    platform:       Model
    standardpar1:   50.0
    standardpar2:   50.000001
    title:          NARR Monthly Means
    dataset_title:  NCEP North American Regional Reanalysis (NARR)
    history:        created 2016/04/12 by NOAA/ESRL/PSD
    references:     https://www.esrl.noaa.gov/psd/data/gridded/data.narr.html
    source:         http://www.emc.ncep.noaa.gov/mmb/rreanl/index.html
    References:     

yrStrt  = 1950          # manually specify for convenience
yrLast  = 2018          # 20th century ends 2018  

clStrt  = 1950          # reference climatology for SOI
clLast  = 1979          

yrStrtP = 1979          # 1st year GPCP
yrLastP = yrLast        # match 20th century

latT = -17.6         # Tahiti
lonT = 210.75  
latD = -12.5         # Darwin 
lonD = 130.83  

# select grids of T and D
T = ds_slp.sel(lat=latT, lon=lonT, method='nearest')
D = ds_slp.sel(lat=latD, lon=lonD, method='nearest')

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-27-6702b30f473f> in <module>
      1 # select grids of T and D
----> 2 T = ds_slp.sel(lat=latT, lon=lonT, method='nearest')
      3 D = ds_slp.sel(lat=latD, lon=lonD, method='nearest')

~\Anaconda3\lib\site-packages\xarray\core\dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
   2004         indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "sel")
   2005         pos_indexers, new_indexes = remap_label_indexers(
-> 2006             self, indexers=indexers, method=method, tolerance=tolerance
   2007         )
   2008         result = self.isel(indexers=pos_indexers, drop=drop)

~\Anaconda3\lib\site-packages\xarray\core\coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs)
    378 
    379     pos_indexers, new_indexes = indexing.remap_label_indexers(
--> 380         obj, v_indexers, method=method, tolerance=tolerance
    381     )
    382     # attach indexer's coordinate to pos_indexers

~\Anaconda3\lib\site-packages\xarray\core\indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance)
    257     new_indexes = {}
    258 
--> 259     dim_indexers = get_dim_indexers(data_obj, indexers)
    260     for dim, label in dim_indexers.items():
    261         try:

~\Anaconda3\lib\site-packages\xarray\core\indexing.py in get_dim_indexers(data_obj, indexers)
    223     ]
    224     if invalid:
--> 225         raise ValueError("dimensions or multi-index levels %r do not exist" % invalid)
    226 
    227     level_indexers = defaultdict(dict)

ValueError: dimensions or multi-index levels ['lat', 'lon'] do not exist